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Probability Theory: Foundation for Data Science に戻る

コロラド大学ボルダー校(University of Colorado Boulder) による Probability Theory: Foundation for Data Science の受講者のレビューおよびフィードバック

4.3
69件の評価

コースについて

Understand the foundations of probability and its relationship to statistics and data science.  We’ll learn what it means to calculate a probability, independent and dependent outcomes, and conditional events.  We’ll study discrete and continuous random variables and see how this fits with data collection.  We’ll end the course with Gaussian (normal) random variables and the Central Limit Theorem and understand its fundamental importance for all of statistics and data science. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from photo by Christopher Burns on Unsplash....

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Probability Theory: Foundation for Data Science: 1 - 22 / 22 レビュー

by Cora M

2021年11月20日

My rating applies to the first week, as I'm dropping after my experience with the first assignment. This is not a commentary on Prof. Dougherty, who seems like a teacher I'd really like to have in an in-person setting. It refers instead to the Gilliamesque homework submission and grading system. Before you join the class, be prepared:

All homework is submitted in an ipynb using an R kernel, and homework is autograded. The grader gives zero feedback regarding what was incorrect, not to mention why or what the correct answer is. All you get is the number of cells that didn't pass; when you reload the assignment, there is no indication of what was wrong.

As a math nerd troll, however, it's magnificent—the grading mechanism itself is a probability problem that provides one with hours of fun. By which I mean frustration.

I joined this class as a refresher, because I love probability. I'm dropping this course before that changes.

by Mattia G

2021年12月18日

peer review assignments are useless

by Essam S

2021年10月11日

The instructor is very good, more examples need to be added, there are mistakes in the evaluation

by Ke M

2021年11月15日

Sorry, but I can't learn R by myself. I know how to do all the calculations, just don't know how to put it in the R language.

by Tim S

2021年9月5日

T​his was a very good course. The material was well thought/planned out such that the readings, lectures, and homeworks built off each other in a constructive manner, which reinforced the material. I highly recommend taking this course as an introduction to probability.

by Jun I

2021年10月13日

Great course which covers from fundamental probability theory with good examples for better understandings.

by Ping Q

2022年1月22日

Very logical arrangement, proper speech rate, crystal clear!

by P A

2022年1月17日

G​reat intro and very well presented by the prof

by Michelle W

2022年4月30日

The professor's instruction is clear and concise, but I wish there were more videos to expand on topics not discussed. The auto-graded assignments are painful since there is no feedback on which problem was wrong (hint: only do one problem at a time and submit to grader. it is painfully slow but this way you know how you did on each question). This course assumes you have basic familiarity with R and can do basic differentiation & integration. I would not recommend this as a first course in probability - this course is best for those who have had some exposure to probability already (E.g., undergraduate level course).

by Nathan H

2022年3月23日

I​t's pretty basic material, but that's not a bad thing. I​ had no trouble with the content.

I​t took a month, or something like that, for Coursera to let do the peer grading that's required by the course.

by Paul R P

2022年4月18日

Need to brush up integral calculus for thios course. Something I haven't looked at for 40 years.

by Kevin H

2022年5月14日

N​ot enough participants for peer review, not quite enough time spent on curriculum

by Michael B

2022年6月16日

This is a great course on probability. Although I felt like it was too easy and should include more PDFs (such as Beta and Gamma) and random variable transformations.

by Mauricio F

2021年7月20日

It was a great course. Good combination between theory and practice.

by 상은 김

2021年10月5日

H​elpful to understand data sciences basic thories

by Daniel C

2022年2月3日

Exactly the probability course I was looking for

by Hidetake T

2022年3月30日

Good course with sufficient amount of practice.

by Claudia G D

2022年3月3日

T​he course is very good.

by Kyle A

2022年2月21日

Great Course!

by Matthew E

2022年5月8日

Lots of fun

by Derek B

2022年6月18日

Overall I thought this course was very good. The lectures were clear. I was even more impressed by the work that was put into designing different kinds of assignments. After completing them, I felt like I understood concepts and techniques much better than before.

That said, I have two big criticisms. First, I really did not like the textbook that was provided. It is supposed to be different from a traditional text book, in a way that makes it easier to understand, I guess. But honestly I thought it had the opposite effect. The non-traditional style made it harder to look up information I wanted to review. I ended up searching for other online sources for better explanations of what was going on.

Second, while I think the class is great on its own, it is part of the Statistical Inference Specialization, and it feels like there was a lack of coordination between the people designing this course and those designing the second course in the series. The second course seems to presuppose much more advanced understanding of probability distributions than this course provides. So while I think the course is great on its own, if you are expecting it to prepare you for the second course in the series, it honestly fails to do so.

by William S

2022年5月25日

I can't get software to run.